The Michael J. Fox Foundation for Parkinson’s Research is committed to equipping researchers with data to accelerate discovery and therapeutic development.
We believe data sharing is critical to research progress. Through our sponsored and funded studies, we collaborate with the research community to collect and distribute a multitude of data resources. You can explore these resources through the platforms below or by searching individual datasets.
Parkinson’s Progression Markers Initiative (PPMI) Data Repository
This comprehensive data repository contains de-identified clinical, imaging, and 'omics data collected through PPMI — a longitudinal study launched in 2010 with the mission of identifying biomarkers of Parkinson’s disease onset and progression. Learn more about the PPMI Data Repository
Data Distribution Platforms
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Fox DEN
The Fox Insight Data Exploration Network (Fox DEN) provides investigators with a tool to explore, download, and analyze patient-reported outcomes and genetic data from the Fox Insight online clinical study.
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AMP PD
The Accelerating Medicines Partnership Parkinson’s Disease (AMP PD) Knowledge Platform harmonizes 'omics and clinical data from several large studies to enable biomarker discovery and validation.
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Synapse
This technology platform, developed by Sage Bionetworks, allows research teams to organize data, track analyses, and collaborate across organizational boundaries.
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CPP
Critical Path for Parkinson’s (CPP) aggregates and analyzes clinical trial data to develop a model for quantitative characterization of Parkinson's progression.
Note: available for Critical Path Institute consortia members only.
Interested In Working with MJFF Data?
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Check out our Getting Started With Parkinson’s Disease Data Guide!
All researchers interested in conducting with research with MJFF-generated data resources are encouraged to review our new guide, which contains information on four datasets: PPMI, GP2, AMP PD, and Fox Insight.
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What’s in the guide?
Each entry contains an overview of the following aspects of these data: study description, study data features, how to access data, intended data uses, data set strengths and limitations, links to pre-existing documentation, plus tips and other considerations for handling these data.
In addition, the guide provides a metatable enabling researchers to at-a-glance gain insight as to which entry might be worth exploring further to determine what data best fits their research purpose, by providing an overview of cohort size, types of analyses it can support, modalities of data available, and the types of clinical features it contains.
